Yuchen Zhu
Machine Learning PhD @ Georgia Tech 🍀
140 Skiles
686 Cherry St NW
Atlanta, GA 30332
Hi, I am Yuchen Zhu, a 2nd year Machine Learning PhD at Georgia Tech.
I work on diffusion models, mean field games, sampling and optimal transport. I am primarily interested in the intersection of dynamics, deep learning and statistics, with application in generative modeling, game theory, scientific machine learning and reinforcement learning.
At Georgia Tech, I am fortunate to be advised by Molei Tao and working with a group of incredible researchers. Prior to that, I graduated with MA in Statistics from Yale University and BS in Honors Mathematics with highest honor from NYU Shanghai. During these times, I had the privilege to work with Zhuoran Yang and Mathieu Laurière on reinforcement learning and mean field games.
Contact: yzhu738 [at] gatech [dot] edu
Updates
[05/2024] New work Plug-and-Play Controllable Generation for Discrete Masked Models is online! |
[05/2024] New work Trivialized Momentum Facilitates Diffusion Generative Modeling on Lie Groups is online! |
[04/2024] New work A Mean-Field Analysis of Neural Stochastic Gradient Descent-Ascent for Functional Minimiax Optimization is online! |
Talks
[11/2024] GT ML Student Seminar |
[10/2024] SIAM Mathematics of Data Science 2024 Atlanta, talk and poster presentation |
[04/2024] Southeast ACM Student Workshop 2024, student presentation |
Selected Publications
- arXivPlug-and-Play Controllable Generation for Discrete Masked ModelsarXiv preprint arXiv:2410.02143, 2024
- arXivDiffusion Generative Modeling for Spatially Resolved Gene Expression Inference from Histology ImagesIn submission, 2024
- arXivTrivialized Momentum Facilitates Diffusion Generative Modeling on Lie GroupsarXiv preprint arXiv:2405.16381, 2024
- arXivA Mean-Field Analysis of Neural Stochastic Gradient Descent-Ascent for Functional Minimax OptimizationarXiv preprint arXiv:2404.12312, 2024